Creating a More Inclusive and Sustainable Future
Biodiversity Entrepreneurship
Review of Finance
We study an emerging class of start-up organizations focused on biodiversity conservation and the challenges they face in financing these ventures. Using a novel machine learning method, we identify 630 biodiversity-linked start-ups in PitchBook and compare their financing dynamics to other ventures. Biodiversity start-ups raise less capital but attract a broader coalition of investors, including not only venture capitalists (“value investors”) but also mission-aligned impact funds and public institutions (“values investors”). Values investors provide incremental capital rather than substituting value investors, but funding gaps persist. We show biodiversity-linked start-ups use social media activity to help connect with value investors. Our findings can inform policy and practice for mobilizing private capital toward biodiversity preservation, emphasizing hybrid financing models and strategic communication.
Sean Cao, Robert H. Smith School of Business, University of Maryland
EPA Scrutiny and Voluntary Environmental Disclosures
Review of Accounting Studies
Market participants have called on the SEC to address the lack of disclosures about firms’ environmental impacts, investments, and exposures. However, the frictions that obstruct the flow of environmental information are not well understood. I shed light on these frictions by examining whether scrutiny by the Environmental Protection Agency (EPA) restricts the firm’s voluntary environmental disclosures in earnings conference calls. Consistent with the notion that EPA scrutiny gives rise to disclosure frictions, I find a negative relation between EPA scrutiny and the environmental disclosures of scrutinized firms. This negative relation is concentrated among firms without environmental expert directors, suggesting that environmental governance mitigates the chilling effect of EPA scrutiny. In terms of disclosure quality, I show that environmental disclosures include fewer quantitative details under EPA scrutiny. Collectively, these findings provide insights into the frictions that restrict the flow of environmental information to market participants, an important issue given the SEC’s efforts to improve current disclosure practices.
Mark Zakota, Assistant Professor, Robert H. Smith School of Business, University of Maryland
Applied AI for finance and accounting: Alternative data and opportunities
February 2024
Big data and artificial intelligence (AI) have transformed the finance industry by altering the way data and information are generated, processed, and incorporated into decision-making processes. Data and information have emerged as a new class of assets, facilitating efficient contracting and risk-sharing among corporate stakeholders. Researchers have also increasingly embraced machine learning and AI analytics tools, which enable them to exploit empirical evidence to an extent that far surpasses traditional methodologies. In this review article, prepared for a special issue on Artificial Intelligence (AI) and Finance in the Pacific-Basin Finance Journal, we aim to provide a summary of the evolving landscape of AI applications in finance and accounting research and project future avenues of exploration. Given the burgeoning mass of literature in this field, it would be unproductive to attempt an exhaustive catalogue of these studies. Instead, our goal is to offer a structured framework for categorizing current research and guiding future studies. We stress the importance of blending financial domain expertise with state-of-the-art data analytics skills. This fusion is essential for researchers and professionals to harness the opportunities offered by data and analytical tools to better comprehend and influence our financial system.
Sean Cao, Associate Professor (with tenure), Robert H. Smith School of Business, University of Maryland, United States of America